RHAIENG-287, #2600: chore(rocm/tf): skip conversion test for the tf2onnx incompatibility with tf 2.16+ (#2604)

Author: jiridanek

jupyter/rocm/tensorflow/ubi9-python-3.12/test/test_notebook.ipynb

@@ -49,9 +49,18 @@
     "        actual_major_minor = get_major_minor(tf.__version__)\n",
     "        self.assertEqual(actual_major_minor, expected_major_minor, \"incorrect version\")\n",
     "\n",
+    "    @unittest.skip(\"https://github.com/onnx/tensorflow-onnx/issues/2329 about Keras 3 incompatibility\")\n",
     "    def test_tf2onnx_conversion(self):\n",
     "        # Replace this with an actual TensorFlow model conversion using tf2onnx\n",
     "        model = tf.keras.Sequential([tf.keras.layers.Dense(1, input_shape=(10,))])\n",
+    "\n",
+    "        # WORKAROUND: known issue https://github.com/onnx/tensorflow-onnx/issues/2319 with tf 2.15+: the conversion would fail with\n",
+    "        #  AttributeError: 'Sequential' object has no attribute 'output_names'. Did you mean: 'output_shape'?\n",
+    "        model.output_names=['output']\n",
+    "\n",
+    "\n",
+    "        # known issue https://github.com/keras-team/keras/issues/18430 with tf 2.15+: the conversion would fail with\n",
+    "        #  AttributeError: 'Sequential' object has no attribute '_get_save_spec'. Did you mean: '_set_save_spec'?\n",
     "        onnx_model = tf2onnx.convert.from_keras(model)\n",
     "\n",
     "        self.assertTrue(onnx_model is not None)\n",